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Are you interested in making the processes for building machine learning models more transparent and explainable? Would you like to work in interdisciplinary teams to uncover the needs of clinical
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, pre-operative determination via endoscopies and imaging remains unreliable for patient selection. The objective of this study is to develop an image-based machine learning prediction model to assess
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Optimization and Machine Learning for Hydrogen Technologies The Natural Computing Group (NACO) at LIACS, Leiden University, is seeking a highly motivated researcher to join our cutting-edge project on AI tool
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) are looking for a: PhD Candidate on Multi-Objective Optimization and Machine Learning for Hydrogen Technologies The Natural Computing Group (NACO) at LIACS, Leiden University, is seeking a highly motivated
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will use the suite of machine learning tools that is readily available in Python packages. In other words, we will not focus on the development of new machine learning tools as everything we need is
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-making processes. This situation underscores the pressing need for advanced machine learning techniques that not only deliver high performance but also provide interpretable insights into how conclusions
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develop novel graph-based machine learning algorithms for state estimation of energy systems. The scientific challenge is to design a real-time state estimator for an active distribution system considering
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Vacancies PhD position on Dependability Driven on Device Learning Algorithms for Embedded Neuromorphic Architectures Key takeaways Edge devices that can learn autonomously while guaranteeing
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faces. At the same time, reinforcement learning is a key technology in artificial intelligence and machine learning that set various state-of-the-art results. In the Reinforcement Learning Lab
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